Virtual Sketch Board with Computer Vision

Abstract

Abstract: As a result, there was a need for a dust-free classroom for children. Thecolor marker then used is detected and mask is produced. It's been really tough to educate scholars on an online platform and make the assignment intriguing during the COVID- 19 epidemic. We're then now, using the ways of computer vision in open cv to make this design. The required language for this design is python due to its further total libraries and easy to make use of the syntax and but understanding the basics as well as it can be enforced in any open cv supported languages The colour shadowing and discovery processes are used to achieve the thing of this design. This program uses hand gestures to give druggies with an intuitive system of Human Computer Interaction( HCI). One multicolored object at the tip of the cutlet is substantially used as the marker. HCI's major thing is to ameliorate mortal- computer commerce. Virtual Sketch is in where we can draw by just landing the stir of a multicolored marker with a camera. corrosion makes the contaminations present in the mask to get reduced and Dilation further regains the eroded main mask. The coming way of morphological operations on the mask produced those are Erosion andDilation.Virtual sketching is a fashion that allows druggies to produce digital delineations or sketches that pretend the appearance of traditional pencil or essay sketches. This can be achieved using OpenCV, an open- source computer vision library, andPython.To produce a virtual sketch, the first step is to read in an image using OpenCV's imread() function. The image is also converted to grayscale using cvtColor() function. This grayscale image will be used as the base for creating thesketch.The coming step is to apply a Gaussian blur to the grayscale image using GaussianBlur() function to smooth out any noise or irregularities in the image. This is followed by using the Canny edge discovery algorithm with the Canny() function to descry the edges of theimage.The edges detected by the Canny algorithm are also thresholded using threshold() function to produce a double image where the edges are shown in white and the background isblack.Finally, to produce the sketch effect, the double image is reversed usingbitwise_not() function, and also the performing image is blended with the original grayscale image usingbitwise_and() function. This will give the appearance of a sketch, where the edges are emphasized and the background islighter.By combining these way, a virtual sketch can be created using OpenCV and Python.